Systematic Review of Life Cycle Greenhouse Gas Emissions ... · Systems (ReEDs) model. Although we...

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Contract No. DE-AC36-08GO28308

Systematic Review of Life Cycle Greenhouse Gas Emissions from Geothermal Electricity Annika Eberle, Garvin Heath, Scott Nicholson, and Alberta Carpenter National Renewable Energy Laboratory

Technical Report NREL/TP-6A20-68474 September 2017

NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory 15013 Denver West Parkway Golden, CO 80401 303-275-3000 • www.nrel.gov

Systematic Review of Life Cycle Greenhouse Gas Emissions from Geothermal Electricity Annika Eberle, Garvin Heath, Scott Nicholson, and Alberta Carpenter National Renewable Energy Laboratory

Prepared under Task No. GTP5.0341

Technical Report NREL/TP-6A20-68474 September 2017

NOTICE

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Acknowledgments This work was supported by the U.S. Department of Energy (DOE) under Contract No. DEAC36-08GO28308 with the National Renewable Energy Laboratory (NREL). Funding for the work was provided by the DOE Office of Energy Efficiency and Renewable Energy, Geothermal Technologies Office. The authors would like to thank Chad Augustine (NREL) and Corrie Clark (Congressional Research Service, formerly of Argonne National Laboratory) for reviewing previous versions of this report. Opinions represented in this report are the authors’ own and do not reflect the view of the DOE or the U.S. government.

iv This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Executive Summary The primary goal of this work was to assess the magnitude and variability of published life cycle greenhouse gas (GHG) emission estimates for three types of geothermal electricity generation technologies: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash, and HT binary. These technologies were chosen to align the results of this report with technologies modeled in National Renewable Energy Laboratory’s (NREL’s) Regional Energy Deployment Systems (ReEDs) model. Although we did gather and screen life cycle assessment (LCA) literature on hybrid systems, dry steam, and two geothermal heating technologies, we did not analyze published GHG emission estimates for these technologies.

In our systematic literature review of the LCA literature, we screened studies in two stages based on a variety of criteria adapted from NREL’s Life Cycle Assessment (LCA) Harmonization study (Heath and Mann 2012). Of the more than 180 geothermal studies identified, only 29 successfully passed both screening stages and only 26 of these included estimates of life cycle GHG emissions. We found that the median estimate of life cycle GHG emissions (in grams of carbon dioxide equivalent per kilowatt-hour generated [g CO2eq/kWh]) reported by these studies are 32.0, 47.0, and 11.3 for EGS binary, HT flash, and HT binary, respectively (Figure ES-1).

Figure ES-1. Life cycle greenhouse gas emissions (GHG) for three types of geothermal electricity: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash and HT binary.

We also found that the total life cycle GHG emissions are dominated by different stages of the life cycle for different technologies. For example, the GHG emissions from HT flash plants are dominated by the operations phase owing to the flash cycle being open loop whereby carbon dioxide entrained in the geothermal fluids is released to the atmosphere. This is in contrast to binary plants (using either EGS or HT resources), whose GHG emissions predominantly originate in the construction phase, owing to its closed-loop process design. Finally, by comparing this review’s literature-derived range of HT flash GHG emissions to data from currently operating geothermal plants, we found that emissions from operational plants exhibit more variability and the median of emissions from operational plants is twice the median of operational emissions reported by LCAs. Further investigation is warranted to better understand the cause of differences between published LCAs and estimates from operational plants and to develop LCA analytical approaches that can yield estimates closer to actual emissions.

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v This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Table of Contents Introduction ................................................................................................................................................. 1 Motivation .................................................................................................................................................... 2 Methodology ................................................................................................................................................ 3 Results and Discussion .............................................................................................................................. 5

Overview of LCA Studies on GHG Emissions from Three Types of Geothermal Electricity ............... 7 Limitations of this Work and Opportunities for Harmonization ............................................................ 7 Summary of Life Cycle GHG Emissions ............................................................................................... 9 GHG Emissions Disaggregated by Life Cycle Phase ........................................................................... 10 Importance of Operational Emissions .................................................................................................. 11

Conclusions ............................................................................................................................................... 13 References ................................................................................................................................................. 15 Appendix. Supplementary Material ......................................................................................................... 20

vi This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

List of Figures Figure ES-1. Life cycle greenhouse gas emissions (GHG) for three types of geothermal electricity:

enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash and HT binary. .................... iv Figure 1. Side-by-side comparison of life cycle greenhouse gas (GHG) emissions from three geothermal

electricity generation technologies: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash and HT binary ............................................................................................................................. 9

Figure 2. Greenhouse gas (GHG) emissions disaggregated by phase of the life cycle (i.e., total, construction, operation, and end of life) for three geothermal electricity generation technologies: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash, and HT binary. .................. 10

Figure 3. Comparison of carbon dioxide (CO2) emissions reported by operational geothermal plants (compiled from Bertani and Thain 2002, Holm et al. 2012, Sullivan and Wang 2013, and Bravi and Basosi 2014) versus GHG emissions computed from life cycle assessments (LCAs) of electricity generated by hydrothermal (HT) flash plants (same values as reported in Figures 1 and 2 above). . 12

vii This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

List of Tables Table 1. Criteria Used to Perform the Second Screen, which Evaluated the Study’s Quality, Transparency,

Completeness, and Relevance .............................................................................................................. 3 Table 2. Studies that Passed both Screens and Produced an Estimate for the Life Cycle Environmental

Impact of Geothermal Technologies .................................................................................................... 6 Table 3. Details about Studies that Passed the Screening Criteria and Produced an Estimate of Life Cycle

Greenhouse Gas (GHG) Emissions for Electricity Produced by Three Types of Geothermal Energy 8 Table A-1. Statistics for Estimates of Total Life Cycle GHG Emissions from Three Types of Geothermal

Electricity: EGS Binary, HT Binary, and HT Flash .......................................................................... 20 Table A-2. Statistics for Estimates of GHG Emissions from the Construction Phase of Three Types of

Geothermal Electricity: EGS Binary, HT Binary, and HT Flash ....................................................... 20 Table A-3. Statistics for Estimates of GHG Emissions from the Operation Phase of Three Types of

Geothermal Electricity: EGS Binary, HT Binary, and HT Flash ....................................................... 20 Table A-4. Statistics for Estimates of GHG Emissions from the End of Life Phase of Three Types of

Geothermal Electricity: EGS Binary, HT Binary, and HT Flash ....................................................... 21 Table A-5. Statistics for Estimates Reported in Figure 3, including the Operational CO2 Emissions

Reported by Geothermal Plants that are Currently Operating and the GHG Emissions Computed via LCA of HT Flash Technology (Same as Column 3 in Table A3) ..................................................... 21

Table A-6. Life Cycle GHG Estimates from the 29 Studies that Passed both Rounds of Screening ......... 21 Table A-7. Sources Screened, with Results for Each Screening Criterion ................................................. 23 Table A-8. Description of Screening Columns ........................................................................................... 29

1 This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Introduction Thermal energy stored in rock, steam, or liquid water can be extracted and used in thermal power plants to produce electricity, heat, or combined heat and power. Although some direct uses of geothermal energy, such as bathing in hot springs, have been used for thousands of years (Cataldi 1999), geothermal power generation technologies were not developed until the early 1900s (Burgassi 1999).

The first geothermal power plant used dry steam that came directly out of a geofield found in Lardarello, Italy. Geothermal power generation methods now include hydrothermal systems and enhanced geothermal systems (EGSs). Hydrothermal (HT) methods bring in-situ geofluids from naturally-occurring geothermal reservoirs to the surface to power a turbo generator either (1) indirectly in a binary cycle plant, which passes the geofluid through a heat exchanger using a secondary working fluid to turn the generator or (2) directly in a flash plant, where the geofluid is vaporized to generate steam which turns the generator. An EGS uses the same power generation method via a turbo generator with binary or flash technology. However, an EGS uses hydraulic stimulation to create fluid connectivity in geothermal systems that do not have adequate water or permeability.

Geothermal energy presents several advantages over other renewable energy technologies, including that it can provide year-round baseload power. However, in 2015, geothermal energy only comprised approximately 0.2% of the world’s primary energy supply (Lund and Boyd 2016, EIA 2016), including 73 terawatt-hours of geothermal electricity (Bertani 2016). Despite the current limited use of geothermal resources, estimates of the global technical potential indicate that geothermal resources could comprise anywhere from 127 exajoules/year to 1,420 exajoules/year, or 25%–280% of the world’s 2008 energy consumption (IPCC 2011). The large range of these estimates is due to variations in technological advances, including the ability to commercialize EGSs, which would allow access to potential resources at greater depths and in more geographic regions.


Motivation With its abundance and reliability, geothermal energy presents opportunities for reducing the world’s dependence on fossil fuels for power and heat generation. In addition, because geothermal power plants have been shown, in almost all cases, to have lower greenhouse gas (GHG) emissions than fossil fuel-fired power plants (Sullivan et al. 2010), they could also help mitigate climate change impacts. However, estimates for the environmental impacts of geothermal power plants vary considerably. In some cases, the estimates of GHGs emitted per kilowatt-hour of geothermal electricity are five to ten times larger than the median values reported for wind and solar technologies (IPCC 2011).

Although authors of many prior studies have performed life cycle assessments (LCAs) to evaluate the environmental impacts of geothermal energy, only two have compared the results from multiple studies (Sullivan et al. 2010; IPCC 2011). Sullivan et al. (2010) developed an LCA for geothermal power plants and compared their results to five other studies, but they did not comprehensively review all available LCAs. Researchers at the National Renewable Energy Laboratory (NREL) systematically reviewed 46 geothermal LCAs in 2011 in support of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) (IPCC 2011). For the 2011 IPCC SRREN, only nine published studies passed the screening process of NREL’s LCA Harmonization Study (Heath and Mann 2012) and, of those, only six provided estimates of life cycle GHG emissions.

Several new LCAs of geothermal technologies have been published since IPCC (2011) and Sullivan et al. (2010). The goal of this work is to build on prior work by incorporating the latest studies in order to decrease the uncertainty around these estimates and increase their value for research and policymaking. Thus, we performed a thorough review of the LCA literature regarding environmental impacts associated with geothermal technologies and then screened the resulting studies using the similar methods to those employed in NREL’s LCA Harmonization Study (Heath and Mann 2012).





Methodology The methods for this current comprehensive literature review were adapted from Heath and Mann (2012) and include a series of two screens. The first screen evaluates whether the study:

• Is written in English;

• Was published after 1980;

• Was published as: o An archival journal article or trade journal article greater than three published

pages in length, o A conference proceeding greater than five double-spaced pages in length, or o A book or book chapter, thesis, dissertation, or report;

• Covers geothermal energy; and

• Reports quantitative results from an LCA or reviews results from multiple LCAs.

The second screen, as outlined in Table 1, evaluates the quality, transparency, completeness, and relevance of the studies that pass the first screen.

Table 1. Criteria Used to Perform the Second Screen, which Evaluated the Study’s Quality, Transparency, Completeness, and Relevance

Category for Second Screen

Criteria

Quality Uses a currently accepted LCA method (e.g., follows guideline 14040 from the International Organization for Standardization (ISO 2006))

Employs a relevant impact assessment method (e.g., selected impact categories, category indicators, and characterization methods)

Evaluates at least two life cycle stages

Transparency and Completeness

Reports their method transparently with regard to key parameters, assumptions and methods (e.g., defines a system boundary)

Provides a numerical description of the system characteristics (e.g., plant size or well depth)

Reports the environmental impact estimates quantitatively

If appropriate, reports the name of LCA software or database used for the analysis

Provides citations for data sources

Reports a unique estimate of the result (i.e., the result is not cited from prior work)

Provides enough information to scale results by plant generation

Relevance Evaluates a modern or near-future system (e.g., supercritical carbon dioxide [CO2] as a working fluid). Geo-pressured geothermal systems were excluded.


After screening the literature, we compiled data from studies that passed all criteria in both screens and also reported estimates of life cycle GHG emissions from geothermal electricity generated by three technology types: EGS binary, HT flash, and HT binary. We did not compile water use estimates from any study because detailed analysis of water use was outside the scope of this work, nor did we compile GHG emission estimates for direct use heating, hybrid, and dry steam systems because those technologies are not modeled within NREL’s Regional Energy Deployment System (ReEDS) model.

For the three types of geothermal electricity investigated, we computed the central tendency and variability in published estimates of GHG emissions for the total life cycle and by life cycle phase (i.e., construction, operation, and end-of-life). If the sample size for the estimates was greater than four, we computed the central tendency using the median and the variability using the interquartile range (i.e., the spread of the middle 50% of the estimates; lower and upper quartiles correspond to the 25th and 75th percentiles respectively) and the total range (i.e., minimum and maximum values). We used these statistics to generate box plots of the total and phase-disaggregated life cycle GHG emissions for the three technology types. These estimates are compatible with ReEDS modeling of life cycle GHG emissions for future power sector deployment scenarios such as for Vision studies performed by the U.S. Department of Energy (DOE) (Wind Vision, Hydropower Vision, etc.) (DOE 2015; DOE 2016).

There are several differences between this report and NREL’s prior harmonization studies of other energy technologies. First, unlike prior NREL harmonization studies, this work only performs a systematic review of the literature and compiles the resulting estimates for life cycle GHG emissions. We do not harmonize the estimates to reflect consistent performance characteristics, life cycle stages, or global warming potentials because such an analysis was outside the scope of this work. Second, to build broad knowledge of the life cycle impacts of geothermal energy, we do not limit our literature survey to only GHG emissions. Instead, we also include studies that report water use (Table 2).




Results and Discussion To build broad knowledge of the life cycle impacts of geothermal energy and to assist future researchers in identifying literature on these topics, we initially performed a literature search, which in addition to identifying LCAs containing estimates of life cycle GHG emissions also identified LCAs containing estimates of life cycle water use. For the same reasons, we also initially searched more broadly on a technology basis than the three geothermal technologies that this report focuses its analysis on. The initial technologies included:

• Electricity generated by 1. EGS binary: EGSs used in the operation of binary cycle power plants, 2. HT binary: HT resources used in binary cycle plants, 3. HT flash: high-temperature HT resources that are vaporized and used in flash

steam plants, 4. Dry steam: steam that directly drives a turbine, and 5. Hybrid systems: the combination or two or more electricity generation

technologies (e.g., geothermal and solar); and

• Heat generated by 6. Combined heat and power: simultaneous production of heat and electricity from

geothermal energy, and 7. Geothermal heat pumps: pumps that transfer heat to or from the ground.

We then focused our analysis on GHG emissions from geothermal electricity and analyzed the three geothermal electricity generation technologies for which multiple LCAs had been performed and which align with the technologies modeled in NREL’s ReEDS model: EGS binary, HT binary, and HT flash.

Of more than 180 geothermal environmental impact studies identified through our systematic review procedures of this literature, only 82 passed the first screen and 29 of those passed the second screen (Table 2). The 29 studies that passed both screens produced more than 40 estimates for two types of environmental impacts – GHG emissions and water use. Three of the studies we identified were included in the comparison performed by Sullivan et al. (2010) (italicized and highlighted in grey in Table 2). Five of the studies were also reported by NREL in the IPCC SRREN (2011) (listed in bold in Table 2).


Table 2. Studies that Passed both Screens and Produced an Estimate for the Life Cycle Environmental Impact of Geothermal Energya

Technology Type Author and Year Publication Type Type of Environmental Impact EGS binary Rogge and Kaltschmitt 2003 Journal article GHG emissions

Bauer et al. 2008 Conference paper GHG emissions Frick et al. 2010 Journal article GHG emissions Clark et al. 2011 Report Water use Clark et al. 2013 Report Water use Heberle et a. 2016 Journal article GHG emissions Lacirignola and Blanc 2013 Journal article GHG emissions Meldrum et al. 2013 Journal article Water use Sullivan et al. 2013 Journal article GHG emissions Sullivan et al. 2014 Report GHG emissions Treyer et al. 2014 Journal article GHG emissions

HT binary Rule et al. 2009 Journal article GHG emissions Clark et al. 2011 Report Water use Clark et al. 2013 Report Water use Meldrum et al. 2013 Journal article Water use Sullivan et al. 2013 Journal article GHG emissions Sullivan et al. 2014 Report GHG emissions Martin-Gamboa et al. 2015 Journal article GHG emissions

HT flash Hondo 2005 Journal article GHG emissions Karlsdottir et al. 2010a Conference paper GHG emissions Clark et al. 2011 Report Water use Skone et al. 2012 Report GHG emissions Clark et al. 2013 Report Water use Marchand et al. 2015 Conference paper GHG emissions Martínez-Corona et al. 2017 Journal article GHG emissions Meldrum et al. 2013 Journal article Water use Sullivan et al. 2013 Journal article GHG emissions Sullivan et al. 2014 Report GHG emissions

Combined heat and power

Karlsdottir et al. 2010b Conference paper GHG emissions Ruzzenenti et al. 2014 Journal article GHG emissions Martin-Gamboa et al. 2015 Journal article GHG emissions

Heat pump Gilli et al. 1999 Report GHG emissions Genchi et al. 2002 Journal article GHG emissions Saner et al. 2010 Journal article GHG emissions Ghafghazi et al. 2011 Journal article GHG emissions Ristimäki et al. 2013 Journal article GHG emissions Russo et al. 2014 Journal article GHG emissions Kim et al. 2015 Journal article GHG emissions Mattinen et al. 2015 Journal article GHG emissions

Hybrid Ristimäki et al. 2013 Journal article GHG emissions Dry steam Buonocore et al. 2015 Journal article GHG emissions

a) Grey coloring and italicized text highlights studies included in the comparison of life cycle greenhouse gas (GHG) emissions from geothermal electricity performed by Sullivan et al. (2010). Bold text corresponds to studies reported in the IPCC SRREN (2011). EGS = enhanced geothermal system, and HT = hydrothermal.


Overview of Estimates of Life Cycle GHG Emissions from Three Types of Geothermal Electricity The primary goal of this work was to evaluate the life cycle GHG emissions associated with the two main types of geothermal energy currently used to generate electricity – hydrothermal (HT) and enhanced geothermal systems (EGS) – because these are the two types of geothermal electricity modeled in NREL’s ReEDS model. As a result, we only extracted raw data from studies passing our screens for three technologies: HT binary, HT flash, and EGS binary. It is important to note that while EGS is considered a viable technology (DOE 2004), it is not yet commercialized and none of the LCA studies that passed our screens examined the total environmental impacts associated with EGS flash.

As shown in Table 3, the location, impact assessment methods, life cycle phases, lifetime, plant size, depth, and temperature evaluated for the three electricity generation technologies vary by study. The locations range from Germany to the United States and Japan, and the primary impact assessment method is based on the global warming potentials reported by the IPCC in 2007. The average operating lifetime is generally between 20 and 30 years, but one study (Rule et al. 2009) assumes 100 years. In addition, while all of these studies include the life cycle phases of construction and operation, some also include the impacts associated with exploratory drilling (exploration) and end-of-life (EOL). Although most studies report results for plant sizes of around 10 megawatts (MW), the sizes range from 900 kilowatts (kW) to 300 MW.

Limitations of this Work and Opportunities for Harmonization As evidenced by the variations in the parameters employed by the LCA studies analyzed here, there are many opportunities for harmonizing the results to use similar global warming potentials, operating lifetimes, plant sizes, and system boundaries, as was done for most generation technologies evaluated in NREL’s LCA Harmonization Study (follow hyperlink for complete list). However, the process of harmonization is outside the scope of this work.

It is also important to note that multiple environmental impact estimates are often reported by a single reference. For example, as indicated in Table 3, there are eighteen life cycle GHG estimates for EGS binary but they only come from seven different studies and ten estimates come from a single study by Lacirignola and Blanc (2013). Although these estimates explore the impact of depth and temperature, having multiple results from a single study may skew the overall results because of similarities in methods.



Table 3. Summary of Studies that Passed the Screening Criteria and Produced an Estimate of Life Cycle GHG Emissions for Three Types of Geothermal Electricity: Enhanced Geothermal Systems (EGS) Binary, Hydrothermal (HT) Binary and HT Flash

Author(s) Year Estimate Count Location Impact Assessment

Methodb

Inclusion of Life Cycle Phasesc

System Lifetime (years)

Size (MW)

Depth (km)

Temp.d

(°C) Explor. Constr. O&M EOL

EGS Binary Technologya Rogge and Kaltschmitt 2003 2 Germany IPCC 1995 - 0.9 3–4.5 150 Bauer et al. 2008 1 Switzerland IPCC 2007 30 36 5.5 150 Frick et al. 2010 2 Europe Frick et al. 2010, Table 1 30 1.75 3.8–4.7 125–150 Lacirignola and Blanc 2013 10 Germany IMPACT 2002+ 25 1–6 2.5–4 145–165 Sullivan et al. 2013 1 United States IPCC 2007 30 20 4–6 150–225 Sullivan et al. 2014 1 United States IPCC 2007 30 20 4–6 150–225 Treyer et al. 2014 1 Switzerland IMPACT 2002+ 20 36 5.5 150 HT Binarya Rule et al. 2009 1 New Zealand CO2 only 100 162 0.66 200 Sullivan et al. 2013 1 United States IPCC 2007 30 50 < 2 150–185 Sullivan et al. 2014 1 United States IPCC 2007 30 10 < 2 150–185 Martin-Gamboa et al. 2015 1 Europe CML-IA 25 2.9 0.725 150–162 Heberle et al. 2016 4 Germany Heberle et al. 2016, Table 2 30 1.75 3.98 127 HT Flasha Hondo 2005 1 Japan IPCC 1995 (CO2 and CH4) 30 55 1 - Karlsdottir et al. 2010a 1 Iceland CML-IA 30 300 2.2 180 Skone et al. 2012 1 United States IPCC 2007 25 50 3.2 182 Sullivan et al. 2013 1 United States IPCC 2007 30 10 1.5–3 175–300 Sullivan et al. 2014 1 United States IPCC 2007 30 50 1.5–3 175–300 Marchand et al. 2015 3 Guadeloupe IPCC 2007 30 16 > 0.5 250–252 Martínez-Corona et al. 2017 1 New Zealand CML 2001 100 162 0.66 260

a) Technology types include enhanced geothermal systems (EGS) using binary technology (EGS binary), hydrothermal (HT) systems using binary technology (HT binary), and HT systems using flash technology (HT flash).

b) Impact assessment methods (global warming potentials) include those reported by IPCC (1995 and 2007), the IMPACT 2002+ method described by Humbert et al. (2014), and the CML-IA method from the Institute for Environmental Sciences at the University of Leiden (CML-IA 2016). The IMPACT 2002+ and the CML-IA methods both use characterization factors reported by the IPCC (2007).

c) The life cycle phases included in each study are indicated with checkmarks. ”Explor.” describes the exploration phase during which exploratory drilling occurs; “Constr.” includes material extraction, processing, and plant construction; O&M refers to operation and maintenance; and EOL refers to end-of-life waste disposal and decommissioning.

d) “Temp.” refers to the temperature of the resource in the ground, not at the surface.


Summary of Life Cycle GHG Emissions Figure 1 shows the central tendency and variability of the life cycle GHG estimates from all studies that passed the first and second screens and reported life cycle GHG emissions for the three technology types examined here: EGS binary, HT flash, and HT binary (the specific studies are listed in Table 1; see Tables A-1 and A-6 in the appendix for summary statistics and raw data). By compiling results from multiple studies, this comprehensive review shows the range and distribution of values reported in the broader literature. However, it is important to note that the estimates reported here are not harmonized estimates because harmonization was outside the scope of this work. The median life cycle GHG emissions from EGS binary, HT flash, and HT binary plants were found to be 32 grams of carbon dioxide equivalent per kilowatt hour (g CO2 eq/kWh), 47 g CO2 eq/kWh, and 11.3 g CO2 eq/kWh respectively (Figure 1; Table A-1).

Figure 1. Side-by-side comparison of life cycle greenhouse gas (GHG) emissions from three geothermal electricity generation technologies: enhanced geothermal systems (EGS) binary,

hydrothermal (HT) flash and HT binary Estimates from Sullivan et al. (2013) are overlaid as dashed red lines with the value for each estimate reported to the right of the line. Refer to Tables A-1 and A-6 in the appendix for summary statistics and raw estimates, respectively. Sample size refers to the number of estimates forming the box plot summary statistics for each technology. (The number of studies reporting those estimates is less than or equal to the number of estimates.)

One of the studies that we analyzed (Sullivan et al. 2013) describes the sources of geothermal GHG emission estimates that are included in Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model, which is used by a variety of stakeholders to evaluate emission impacts of advanced vehicle and fuel technologies. As a result, we compared the results from our literature review to the data reported by Sullivan et al. (2013) (dashed lines in Figure 1 correspond to data from Sullivan et al. [2013]). While the estimates from Sullivan et al. (2013) are within the range of estimates for all three technologies explored here, they are close to the first quartile of the literature estimates for HT binary and EGS binary and the upper quartile of the literature estimates for HT flash. Thus, there is an opportunity for updates to be made to the estimates of life cycle GHG emissions within the GREET model.

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GHG Emissions Disaggregated by Life Cycle Phase Of the three geothermal electricity generation technologies examined in this report, HT flash exhibits the largest amount of variation in total life cycle GHG emissions (Figure 1). While the range for total emissions from EGS binary is 16.9–79 g CO2 eq/kWh, the range of HT flash is 15.0–245 g CO2 eq/kWh. When the emissions are disaggregated by phase, as in Figure 2, it is apparent that most of the variability in emissions from HT flash comes from plant operation, which is the largest contributor to the total emissions from HT flash plants. The large operational emissions from HT flash plants result from the release of non-condensable gases when the geofluid in a flash plant is exposed to the atmosphere after it passes through a turbine. Neither EGS binary systems nor HT binary systems have emissions associated with non-condensable gases because the geofluids in binary geothermal plants remain in a closed-loop system. However, the operational emissions associated with hydrothermal flash plants range widely depending on the efficiency of the plant and composition of the geofluid, which varies with location and depth.

Figure 2. Greenhouse gas (GHG) emissions disaggregated by phase of the life cycle (i.e., total, construction, operation, and end of life) for three geothermal electricity generation technologies: enhanced geothermal systems (EGS) binary, hydrothermal (HT) flash, and

HT binary. Sample size refers to the number of estimates forming the box plot summary statistics for each technology. (The number of studies reporting those estimates is less than or equal to the number of estimates.)

* Several studies only report estimates of total life cycle GHG emissions (they do not disaggregateemissions by phase but they do report which life cycle phases are included in their estimates oftotal emissions). As a result, the sample size of total life cycle GHG emission estimates is largerthan the sample size of estimates disaggregated by life cycle phase (e.g., for EGS binary, thesample size of estimates for total emissions is 18 while the sample size for construction is 8). Sinceper-phase emission estimates are a subset of the estimates that provide total emission estimatesand the estimates of total emissions from the per-phase and total-only sources differ, the mediansof the per-phase GHG emission estimates might be greater than the median of the total.

EGS Binary HT Flash HT Binary

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On the other hand, construction is the major contributor to total life cycle GHG emissions from EGS binary and HT binary. Because the EGS binary wells assumed in the LCA studies are two to five times deeper than HT binary wells, they require more material for construction. EGS systems also require diesel power for the hydraulic stimulation and often involve more production and injection wells (Sullivan et al. 2014). Thus, the emissions from the construction of EGS binary plants are much higher than those for HT binary plants.

Importance of Operational Emissions Several of the geothermal LCA studies we reviewed discussed the large contribution of and the variability associated with the operational emissions from HT flash plants (Sullivan et al. 2011; Sullivan et al. 2012; Sullivan et al. 2013; Sullivan and Wang 2013; and Sullivan et al. 2014). In particular, these studies referenced a survey conducted by Bertani and Thain (2002) to assess the worldwide operational emissions from HT flash plants. From this survey, Bertani and Thain reported a weighted average of 122 grams of carbon dioxide per kilowatt hour (g CO2/kWh) and a range of 4–740 g CO2/kWh for operational emissions from geothermal electricity. Even without including the emissions from other types of GHGs, such as methane and nitrous oxide, the maximum amount of carbon dioxide reportedly emitted (in grams per kilowatt hour) is greater than some estimates for the total GHG emissions from natural gas power plants; the median of harmonized estimates of life cycle GHG emissions for electricity generated by a natural gas combustion turbine is 450 g CO2 eq/kWh (O'Donoughue et al. 2014).

Many of the studies we reviewed also discuss the variability in operational emissions from flash plants in California (Sullivan et al. 2011, 2012, 2013, 2014; Sullivan and Wang 2013). For example, Sullivan et al. (2014) collected data from the California Environmental Protection Agency and found that the operational GHG emissions from HT flash plants in California had a weighted average of 103 g CO2 eq/kWh in 2012, with 85% of the plants emitting below 170 g CO2 eq/kWh and only two plants emitted more than 300 g CO2 eq/kWh.

To better describe how the emissions from actual geothermal power plants compare with the GHG emissions computed from the LCA studies we reviewed, we compiled data from four studies reporting operational emissions from actual power plants: Bertani and Thain (2002), Holm et al. (2012), Sullivan and Wang (2013), and Bravi and Basosi (2014). The results of this review are illustrated in the left column of Figure 3, which shows the range of operational emissions from geothermal power plants, most of which use HT flash technology. Rather than reporting total GHG emissions, these four studies only describe emissions from one GHG, carbon dioxide because this is the only GHG for which operational emissions are reported.

12

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Figure 3. Comparison of carbon dioxide (CO2) emissions reported by operational geothermal plants (compiled from Bertani and Thain 2002, Holm et al. 2012, Sullivan and Wang 2013, and Bravi and Basosi 2014) versus GHG emissions computed from life cycle

assessments (LCAs) of electricity generated by hydrothermal (HT) flash plants (same values as reported in Figures 1 and 2 above).

Sample size refers to the number of estimates forming the box plot summary statistics for each technology. (The number of studies reporting those estimates is less than or equal to the number of estimates.)

It is clear from these studies that operational emissions from geothermal flash plants vary widely and may be up to ten times greater than those estimated from the LCA studies examined here. However, because the amount of non-condensable gases emitted during operation varies with multiple parameters, including geographic location, well depth, and resource temperature, and these system characteristics differ across the LCA studies and the operational studies, one would need to ensure a consistent set of system characteristics in order to perform a fair comparison of the emissions reported from operational studies and LCAs. Such a comparative analysis is beyond the scope of this work but more research needs to be done to quantify the relationships among resource location, geofluid composition, and GHG emissions. Furthermore, because most flash power plants are located in areas where natural geothermal resources (e.g., hot springs and geysers) already occur and because these areas may have a background level of GHGs from “natural” emissions, identifying the emissions of anthropogenic geothermal systems could be difficult. Thus, more work also needs to be done to identify the difference between natural and geothermal electricity-induced GHG emissions.

0

200

400

600

Reported byOperational

Geothermal Plants

Computedvia LCA ofHT Flash

Em

issi

on

s D

urin

g P

lan

t Op

era

tion

(g C

O2/

kWh

)

4 8Sample Size:

Box Plot Key

Lower quartile

Median

Upper quartile

Minimum

Maximum


Conclusions We performed a systematic review of the LCA literature on geothermal energy, evaluating the quality, completeness, transparency, and relevance of over 180 geothermal environmental impact studies. We identified 29 LCA studies on geothermal energy that passed our rigorous screening methodology. These studies included assessments for the GHG emissions and water use associated with geothermal electricity generation, heat generation, and combined heat and power. We then examined three electricity generation technologies (i.e., EGS binary, HT binary, and HT flash) in detail and compiled published estimates for life cycle GHG emissions.

There are several limitations of this work. First, we only examine the GHG emissions associated with three geothermal technologies that generate electricity. There are other types of geothermal technologies, including those that produce heat for heating purposes, that could be addressed in future research. Second, the results presented here only represent an examination of one environmental impact category: climate change (as measured by life cycle GHG emissions). Numerous other impact categories, such human toxicity, land use, and resource consumption would need to be examined to gain a more comprehensive understanding of the life cycle environmental impacts of geothermal electricity. Third, the results presented here do not represent the distribution of likelihood for actual life cycle GHG emissions from geothermal electricity. As evidenced by the comparison of operational emissions, the results compiled from these LCAs may not represent all possible variations in parameters associated with geothermal energy. Finally, the results presented here are published estimates, not adjusted for consistency in methods or underlying assumptions, as has been completed for many other generation technologies in NREL’s LCA Harmonization Project. There are several inconsistencies among the estimates that we compiled for life cycle GHG emissions. For example, these studies comprise a wide variety of geographic regions, well depths, and temperatures; they also use different impact assessment methods, characterization factors, operating lifetimes, and system boundaries. A complete harmonization of these studies would provide a more consistent estimate of central tendency for life cycle GHG emissions of these geothermal generation technologies.

Despite these limitations, our analysis revealed that, of the three geothermal electricity generation technologies considered, HT flash generates the most GHG emissions per kilowatt hour of electricity (median of 47 g CO2 eq/kWh). These median GHG emissions from HT flash were nearly 50% greater than the median for EGS binary and over four times greater than median for HT binary. Furthermore, while most of the GHG emissions from HT binary and EGS binary are associated with the construction of these technologies, GHG emissions from HT flash primarily result from operation of the facility. These operational emissions result from the open-loop nature of HT flash technology, which releases non-condensable gases when the geofluid is exposed to the atmosphere.

The variability in operational GHG emissions from geothermal power plants presents a challenging problem for computing the technology’s impact on climate change. We show that the median CO2 emissions reported by operational geothermal plants are approximately two times larger than the median LCA estimates of GHG emissions from the operation of HT flash plants. Because the operational emissions of geothermal plants vary widely with system characteristics (e.g., local geology, depth, temperature), the differences in operational emissions reported by LCAs and operational studies are likely a result of differences in the system



characteristics that are used in these studies. A better understanding of the distribution of non-condensable gases in geothermal reservoirs, as well as the effects of reservoir depletion and repressurization on GHG emissions profiles over time, would improve estimates of life cycle GHG emissions from geothermal plants.

Overall, we show that there are large variations in the life cycle GHG emissions from three types of geothermal technologies that generate electricity: HT flash, HT binary, and EGS binary. The median estimates for HT binary and EGS binary technologies generate less than 40 g CO2 eq/kWh, which represents the same order as most other renewable energy technologies (IPCC 2011). However, the median value in the literature for HT flash is slightly higher (47 g CO2 eq/kWh), and the range of literature and operational emissions from this technology indicate it may generate three to ten times more GHG emissions than other renewable energy technologies. Because EGSs are still in the development and demonstration phase, the estimate for GHG emissions from EGS binary might change once the technology is commercialized. On the other hand, HT binary is a more mature technology than EGS binary and appears to have the lowest life cycle GHG emissions of the three types of geothermal electricity generation technologies examined here.


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Appendix. Supplementary Material Table A-1. Total Life Cycle GHG Emissions from Three Types of Geothermal Electricity: EGS

Binary, HT Binary, and HT Flasha

EGS Binary HT Flash HT Binary All Technologies Min (g CO2 eq/kWh) 16.9 15.0 5.6 5.6 Quartile 1 (g CO2 eq/kWh) 27.2 39.4 5.8 21.9 Median (g CO2 eq/kWh) 32.0 47.0 11.3 36.7 Quartile 3 (g CO2 eq/kWh) 47.5 118.4 38.5 51.5 Max (g CO2 eq/kWh) 79.0 245.2 97.2 245.2 Sample size 18 9 8 35

a) These values were computed from the estimates obtained from the studies that passed both of our literature screens. EGS Binary = enhanced geothermal systems used in the operation of binary cycle power plants, HT binary = hydrothermal (HT) resources used in binary cycle plants, and HT flash = high temperature HT resources that are vaporized in flash steam plants.

Table A-2. GHG Emissions from the Construction Phase of Three Types of Geothermal Electricity: EGS Binary, HT Binary, and HT Flasha

EGS Binary HT Flash HT Binary All Technologies

Min (g CO2 eq/kWh) 23.0 3.9 5.7 3.9

Quartile 1 (g CO2 eq/kWh) 27.7 4.1 8.0 5.2

Median (g CO2 eq/kWh) 39.9 5.0 15.0 15.3


Max (g CO2 eq/kWh) 71.1 5.3 20.5 71.1

Sample size 8 7 6 21 a) These values were computed from the estimates obtained from the studies that passed both of our literature screens. EGS

Binary = enhanced geothermal systems used in the operation of binary cycle power plants, HT binary = hydrothermal (HT) resources used in binary cycle plants, and HT flash = high temperature HT resources that are vaporized in flash steam plants.

Table A-3 GHG Emissions from the Operation Phase of Three Types of Geothermal Electricity: EGS Binary, HT Binary, and HT Flasha


Min (g CO2 eq/kWh) 0.0 9.7 0.0 0.0


Median (g CO2 eq/kWh) 2.5 73.2 0.9 6.9


Max (g CO2 eq/kWh) 7.5 240.2 76.8 240.2

Sample size 8 8 7 23 a) These values were computed from the estimates obtained from the studies that passed both of our literature screens. EGS



Table A-4. GHG Emissions from the End of Life Phase of Three Types of Geothermal Electricity: EGS Binary, HT Binary, and HT Flasha


Min (g CO2 eq/kWh) 0.15 - 0.04 0.04

Quartile 1 (g CO2 eq/kWh) 0.16 - 0.04 0.07

Median (g CO2 eq/kWh) 0.21 - 0.06 0.12

Quartile 3 (g CO2 eq/kWh) 0.29 - 0.08 0.18

Max (g CO2 eq/kWh) 0.40 - 0.08 0.40

Sample size 4 - 4 8 a) These values were computed from the estimates obtained from the studies that passed both of our literature screens. EGS


Table A-5. CO2 Emissions from the Operation Phase of Active Geothermal Plants Compared to GHG Emissions Computed via LCA of HT Flash Technologya

CO2 Emissions Reported by

Operational Plants

GHG Emissions Computed via

LCA of HT Flash

Min (g CO2 eq/kWh) 110.0 9.7

Quartile 1 (g CO2 eq/kWh) 119.0 34.6

Median (g CO2 eq/kWh) 151.0 73.2

Quartile 3 (g CO2 eq/kWh) 307.6 118.3

Max (g CO2 eq/kWh) 690.2 240.2

Sample size 4 8 a) Emissions from operational plants were compiled from Bertani and Thain (2002), Holm et

al. (2012), Sullivan and Wang (2013), and Bravi and Basosi (2014). GHG emissions computed via LCA were obtained from the studies that passed both of our literature screens (see Column 3 of Table A-3). The data in Table A-5 were used to generate Figure 3.


Table A-6. Life Cycle GHG Estimates from the 29 Studies that Passed both Rounds of Screening

Author(s) Year Technology Emissions (g CO2eq / kWh) Total Constr. Oper. EOL

Rule et al. 2009 HT binary 5.6 - - - Sullivan et al. 2013 HT binary 5.7 5.7 0 - Martin-Gamboa et al. 2015 HT binary 5.79 - - - Sullivan et al. 2014 HT binary 6.4 5.7 0.72 - Heberle et al. 2016 HT binary 89.2 14.7 74.4 0.04 Heberle et al. 2016 HT binary 16.1 15.3 0.8 0.04 Heberle et al. 2016 HT binary 97.2 20.3 76.8 0.08 Heberle et al. 2016 HT binary 21.6 20.5 1 0.08 Lacirignola and Blanc 2013 EGS binary 16.9 - - - Lacirignola and Blanc 2013 EGS binary 21.8 - - - Lacirignola and Blanc 2013 EGS binary 22 - - - Treyer et al. 2014 EGS binary 24 23 1 - Bauer et al. 2008 EGS binary 27 - - - Sullivan et al. 2013 EGS binary 27.7 27.7 0 - Lacirignola and Blanc 2013 EGS binary 28.6 - - - Lacirignola and Blanc 2013 EGS binary 29.2 - - - Lacirignola and Blanc 2013 EGS binary 29.3 - - - Sullivan et al. 2014 EGS binary 34.6 27.7 6.89 - Lacirignola and Blanc 2013 EGS binary 36.7 33.03 3.67 - Lacirignola and Blanc 2013 EGS binary 37.9 - - - Lacirignola and Blanc 2013 EGS binary 40.4 - - - Lacirignola and Blanc 2013 EGS binary 49.8 - - - Frick et al. 2010 EGS binary 51 49.827 1.02 0.153 Rogge and Kaltschmitt 2003 EGS binary 52 46.8 4.94 0.26 Frick et al. 2010 EGS binary 53 51.516 1.325 0.159 Rogge and Kaltschmitt 2003 EGS binary 79 71.1 7.505 0.395 Karlsdottir et al. 2010a HT flash 40 - - - Hondo 2005 HT flash 15 5.3 9.7 - Sullivan et al. 2014 HT flash 109 4.1 104.51 - Sullivan et al. 2013 HT flash 126.1 4.1 122 - Skone et al. 2012 HT flash 245.2 5 240.2 - Marchand et al. 2015 HT flash 47 5.17 41.83 - Marchand et al. 2015 HT flash 38.5 3.85 34.65 - Marchand et al. 2015 HT flash 39.4 5.122 34.278 - Martínez-Corona et al. 2017 HT flash 118.35 - 117 -


Table A-7. Studies Screened, with Results for Each Screening Criterion “Y” (yes) indicates that the source met the requirement, while “N” (no) means it did not pass. A “−” indicates that the criterion was not applicable for that study. A “Y” in column P1 (P2) indicates that the study passed the first (second) screen. The table is sorted first on whether the sources passed the first screen, then whether they passed the second screen, then alphabetically. A description of each screening column is presented in Table A-8.

Literature First Screen Second Screen

Author(s) Year A B C D E F G P1 H I J K L M N O P Q R P2

Bauer et al. 2008 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Buonocore et al. 2015 Y Y Y Y Y Y − Y Y Y − Y Y Y − Y Y Y Y Y

Clark et al. 2013 Y Y Y Y Y Y − Y Y Y Y Y Y Y − Y Y Y Y Y

Clark et al. 2011a Y Y Y Y Y Y − Y Y Y Y Y Y Y − Y Y Y Y Y

Frick et al. 2010 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Genchi et al. 2002 Y Y Y Y Y Y − Y Y Y Y Y Y Y − Y Y Y Y Y

Ghafghazi et al. 2011 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Gilli et al. 1999 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Heberle et al 2016 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Hondo 2005 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

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Rogge and Kaltschmitt 2003 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

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Russo et al. 2014 Y Y Y Y Y Y − Y Y Y Y Y Y Y − Y Y Y Y Y

Ruzzenenti et al. 2014 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Saner et al. 2010 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Skone et al. 2012 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Sullivan et al. 2014 Y Y Y Y Y Y − Y Y Y Y Y Y Y − Y Y Y Y Y

Sullivan et al. 2013 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y




Treyer et al. 2014 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y Y

Abusoglu and Sedeeq 2013 Y Y Y Y Y Y − Y Y Y − Y Y Y Y Y Y N Y N

Amponsah et al. 2014 Y Y Y Y Y Y − Y N N − − − − − − − − − N

Asdrubali et al. 2015 Y Y Y Y Y Y − Y Y Y − Y Y N − − − − − N

Bauer et al. 2010 Y Y Y Y Y Y − Y Y Y − − − − − − − N − N

Benke and Patzay 2010 Y Y Y Y Y Y − Y Y Y − Y Y Y Y Y Y N Y N

Bonamente et al. 2015 Y Y Y Y Y Y − Y Y Y Y N Y Y Y Y Y Y N N

Bravi and Basosi 2014 Y Y Y Y Y Y − Y N Y − Y Y Y − Y Y Y Y N

Brown and Ulgiati 2002 Y Y Y Y Y Y − Y N − − − − − − − − − − N

Clark and Harto 2012 Y Y Y Y Y Y − Y Y Y Y Y Y N − − − − − N

Clark, Harto, and Troppe 2011 Y Y Y Y Y Y − Y Y Y − Y Y Y − Y Y Y N N

Evans and Strezov 2010 Y Y Y Y Y Y − Y N N − − − N − − − − − N

Evans et al. 2009 Y Y Y Y Y Y − Y N N − − − − − − − − − N

Frank et al. 2012 Y Y Y Y Y Y − Y Y Y − Y Y Y Y Y Y Y N N

Frick et al. 2007 Y Y Y Y Y Y − Y Y Y − N Y Y Y Y N Y Y N

Fthenakis and Kim 2010 Y Y Y Y Y Y − Y N N − − − N − − − − − N

Gerber and Marechal 2012 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y N Y Y N

Huang and Mauerhofer 2015 Y Y Y Y Y Y − Y N − − − − − − − − − − N

IEA 1998 Y Y Y Y Y Y − Y Y Y − Y Y Y − N Y Y Y N

Jacobson 2009 Y Y Y Y Y Y − Y N N − − − − − − − − − N

Karlsdottir et al. 2015 Y Y Y Y Y Y − Y Y N − Y Y Y − Y Y Y Y N

Kayser and Kaltschmitt 1997a Y Y Y Y Y Y − Y Y N − N N Y N Y Y Y Y N

Kenny et al. 2010 Y Y Y Y Y Y − Y N N − − − N − − − − − N

Kim and Fthenakis 2008 Y Y Y Y Y Y − Y Y − − − − N − − − − − N

Koroneos 2007 Y Y Y Y Y Y − Y Y Y − Y Y N − Y Y Y Y N

Lacirignola et al. 2017 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y N N Y N

Macknick et al. 2012 Y Y Y Y Y Y − Y N Y − Y Y N − N Y Y Y N

Martin 1997 Y Y Y Y Y Y − Y Y Y − Y Y Y Y N Y Y Y N

Matuszewska 2011 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y N Y Y N

Nitkiewicz and Sekret 2014 Y Y Y Y Y Y − Y Y N − Y Y Y Y Y Y N Y N

Pehnt 2006 Y Y Y Y Y Y − Y Y Y − Y Y Y Y N Y Y Y N

Rodriguez et al. 2012 Y Y Y Y Y Y − Y Y Y − N N Y N Y Y Y Y N




San Martin 1989 Y Y Y Y Y Y − Y N N − − − − − − − − − N

Santoyo-Castelazo et al. 2011 Y Y Y Y Y Y − Y Y Y − N Y Y Y Y N Y Y N

Schroeder, Harto, et al. 2014 Y Y Y Y Y Y − Y N Y − N − − − − − − − N

Schroeder, Clark, and Harto 2014 Y Y Y Y Y Y − Y N − − − − − − − − − − N

Sovacool 2008 Y Y Y Y Y Y − Y Y Y Y Y Y N − − − − − N

Sullivan et al. 2011 Y Y Y Y Y Y − Y Y Y Y Y Y Y − Y Y Y N N

Sullivan et al. 2012 Y Y Y Y Y Y − Y Y Y Y Y Y N − Y Y Y Y N

Sullivan et al. 2010 Y Y Y Y Y Y − Y Y Y Y Y Y Y Y Y Y Y Y N

Sullivan and Wang 2013a Y Y Y Y Y Y − Y N Y − Y Y N Y Y Y Y Y N

Sullivan and Wang 2013b Y Y Y Y Y Y − Y Y Y − Y Y N N N N Y Y N

Tolba and ElMahgary 1985 Y Y Y Y Y Y − Y N Y − N Y Y − Y Y Y Y N

Treyer and Bauer 2010 Y Y Y Y Y Y − Y Y Y − N − − − − − − − N

Uchiyama 1997 Y Y Y Y Y Y − Y N N − N N Y − Y Y Y Y N

Uchiyama 2007 Y Y Y Y Y Y − Y Y N − N N − − − − − − N

Chiavetta et al. 2011 Y Y Y Y Y Y − Y Y Y − N − − − − − − − −

Clark and Harto 2013 Y Y Y Y Y Y − Y Y Y − N − − − − − − − −

Gudikson 1989 Y Y Y Y Y N − N N N − − − − − − − − − N

Guo et al. 2013 Y Y Y Y Y Y − Y Y Y − Y N − − − − − − −

Haddad and Dones 1991 Y Y Y Y Y N − N N N − − − − − − − − − N

Herendeen and Plant 1981 Y Y Y Y Y N − N N N − Y Y Y − Y N Y Y N

Hienuki et al. 2015 Y Y Y Y Y Y − Y N − − − − − − − − − − −

Kammen and Pacca 2004 Y Y Y Y Y Y − Y N − − − − − − − − − − −

Adee and Moore 2010 Y Y N − − − − N − − − − − − − − − − − −

Akai et al. 1997 Y Y Y Y N − − N − − − − − − − − − − − −

Armannsson et al. 2005 Y Y Y Y Y N − N − − − − − − − − − − −

Arslan 2010 Y Y Y Y Y N − N − − − − − − − − − − − −

Azim et al. 2010 Y Y N − − − − N − − − − − − − − − − − −

Barbier 2002 Y Y Y Y Y N − N − − − − − − − − − − − −

Barfield 2006 Y Y Y Y Y N − N − − − − − − − − − − − −

Bayer et al. 2013 Y Y Y Y Y N − N − − − − − − − − − − − −

Bayer et al. 2012 Y Y Y Y Y N − N − − − − − − − − − − − −

Bertani and Thain 2002 Y Y N Y Y N − N − − − − − − − − − − − −




Bloomfield and Moore 1999 Y Y Y Y Y N − N − − − − − − − − − − −

Bloomfield et al. 2003 Y Y N Y Y N − N − − − − − − − − − − − −

Booth and Neil 1998 Y Y N − − − − N − − − − − − − − − − − −

Boran 2013 Y Y Y Y Y N − N − − − − − − − − − − − −

Brophy 1997 Y Y Y Y Y N − N − − − − − − − − − − − −

Brugman et al. 1995 Y Y Y Y Y N − N − − − − − − − − − − − −

Canelli et al. 2015 Y Y Y Y Y N − N − − − − − − − − − − − −

Carvalho et al. 2015 Y Y Y Y Y N − N − − − − − − − − − − − −

Chamorro et al. 2012 Y Y Y Y Y N − N − − − − − − − − − − − −

Clark et al. 2009 Y Y Y Y Y N − N − − − − − − − − − − − −

Clark et al. 2011b Y N Y Y Y N − N − − − − − − − − − − − −

Clark et al. 2014 Y Y Y Y Y N − N − − − − − − − − − − − −

DiPippo 1988 Y Y N − − − − N − − − − − − − − − − − −

DiPippo 2008 Y Y Y Y Y N − N − − − − − − − − − − −

Dones et al. 2007 Y Y Y Y N Y − N − − − − − − − − − − −

Dones et al. 1999 Y N Y Y N − − N − − − − − − − − − − − −

Dones et al. 2005 Y Y Y Y N − − N − − − − − − − − − − − −

Dotzauer 2010 Y Y Y Y Y N − N − − − − − − − − − − − −

Eggertson 2004 Y Y N − − − − N − − − − − − − − − − − −

Ekrami and Sadeghi 2009 Y N Y N − − − N − − − − − − − − − − − −

El-Emam and Dincer 2013 Y Y Y Y Y N − N − − − − − − − − − − − −

Falcone and Borggard 1991 Y Y N Y Y N − N − − − − − − − − − − − −

Feck and Wagner 2008 Y Y Y N Y Y − N − − − − − − − − − − − −

Frick and Kaltschmitt 2009 Y N Y N − − − N − − − − − − − − − − − −

Frischknecht et al. 2009 Y Y Y Y N N − N − − − − − − − − − − − −

Gagnon et al. 2002 Y Y Y Y N Y − N − − − − − − − − − − − −

Ganjehsarabi et al. 2012 Y Y Y Y Y N − N − − − − − − − − − − − −

Geothermal Technologies Office 2008 Y Y Y Y Y N − N − − − − − − − − − − − −

Hadian and Madani 2015 Y Y Y Y Y N − N − − − − − − − − − − −

Hamamatsu 2003 Y Y Y N − − − N − − − − − − − − − − − −

Hamamatsu et al. 2004 Y Y Y Y Y N − N − − − − − − − − − − − −

Hammons 2007 Y Y Y Y Y N − N − − − − − − − − − − −




Harto and Clark 2012 Y Y Y Y Y N − N − − − − − − − − − − − −

Harto et al. 2014 Y Y Y Y Y N − N − − − − − − − − − − − −

Holm et al. 2012 Y Y Y Y Y N − N − − − − − − − − − − −

Hunt 2001 Y Y Y Y Y N − N − − − − − − − − − − − −

Inhaber 2004 Y Y Y Y Y N − N − − − − − − − − − − − −

Iwaoka et al. 2008 Y N Y N Y Y − N − − − − − − − − − − − −

Jensen 2007 Y N Y N Y − − N − − − − − − − − − − − −

Joblin 2005 Y Y Y Y Y N − N − − − − − − − − − − − −

Kabassi and Cho 2012 Y N Y Y N − − N − − − − − − − − − − − −

Kagel 2008 Y Y Y Y Y N − N − − − − − − − − − − − −

Kagel and Gawell 2005 Y Y Y Y Y N − N − − − − − − − − − − − −

Kagel et al. 2007 Y Y Y Y Y N − N − − − − − − − − − − − −

Kayser and Kaltschmitt 1997b Y Y Y N − − − N − − − − − − − − − − − −

Kim et al. 2013 Y Y Y Y Y N − N − − − − − − − − − − − −

Klein and Whalley 2015 Y Y Y Y Y N − N − − − − − − − − − − − −

Koroneos and Roumbas 2012 Y Y Y Y Y N − N − − − − − − − − − − − −

Koroneos and Tsarouhis 2012 Y Y Y Y N Y − N − − − − − − − − − − − −

Kummert et al. 2006 Y Y Y Y Y N − N − − − − − − − − − − − −

Kutscher and Costenaro 2002 Y Y Y Y Y N − N − − − − − − − − − − − −

Lacirignola et al. 2014 Y Y Y Y Y N − N − − − − − − − − − − −

Layton and Pimentel 1980 Y Y Y Y Y N − N − − − − − − − − − − − −

Levi et al. 2003 Y Y Y Y Y N − N − − − − − − − − − − − −

Liu et al. 2008 Y Y N Y Y Y − N − − − − − − − − − − − −

Lovekin 1988 Y Y Y Y Y N − N − − − − − − − − − − − −

Lux and Kaltschmitt 1997 Y Y Y N − − − N − − − − − − − − − − − −

Macknick et al. 2011 Y Y Y Y Y N − N − − − − − − − − − − −

Mahon et al. 1980 Y Y Y Y Y N − N − − − − − − − − − − − −

Mansure 2011 Y Y N Y − − − N − − − − − − − − − − − −

Mason et al. 2010 Y Y Y Y Y N − N − − − − − − − − − − − −

McCulloch et al. 2003 Y Y Y Y Y N − N − − − − − − − − − − − −

McFarlane et al 2012 Y Y Y Y Y N − N − − − − − − − − − − − −

Menberg et al. 2016 Y Y Y Y Y N − N − − − − − − − − − − − −




Miller 1996 Y Y N Y Y N − N − − − − − − − − − − − −

Mirasgedis and Diakouaki 1997 Y Y Y Y N N − N − − − − − − − − − − − −

Mohan et al. 2015 Y Y Y Y Y N − N − − − − − − − − − − −

Morrissey et al. 2004 Y Y Y Y N − − N − − − − − − − − − − − −

Nill, M. 2004 Y N Y N − − − N − − − − − − − − − − − −

Onat and Bayar 2010 Y Y Y Y Y N − N − − − − − − − − − − − −

Pfister et al. 2011 Y Y Y Y Y N − N − − − − − − − − − − − −

Rentizelas and Georgakellos 2014 Y Y Y Y Y N − N − − − − − − − − − − − −

Rice 1980 Y Y Y Y Y N − N − − − − − − − − − − − −

Roth and Ambs 2004 Y Y Y Y N N − N − − − − − − − − − − − −

Sabonnadiere et al. 2007 Y N Y N Y − − N − − − − − − − − − − − −

Sakurai et al. 2011 Y Y Y Y Y N − N − − − − − − − − − − −

Saner et al. 2014 Y Y Y Y Y N − N − − − − − − − − − − −

Schroeder et al. 2013 Y Y Y Y Y N − N − − − − − − − − − − − −

Sivasakthivel et al. 2015 Y Y Y Y Y N − N − − − − − − − − − − − −

Sovacool 2010 Y Y Y Y Y N − N − − − − − − − − − − − −

Tomasini-Montenegro et al. 2016 Y Y Y Y Y N − N − − − − − − − − − − − −

Twidell and Weir 1986 Y Y Y Y Y N − N − − − − − − − − − − − −

Uchiyama 1994 Y N − − − Y − N − − − − − − − − − − − −

Uchiyama 1996a Y Y Y Y N − − N − − − − − − − − − − − −

Uchiyama 1996b Y Y Y Y N − − N − − − − − − − − − − − −

van de Vate 1994 Y Y Y Y N − − N − − − − − − − − − − − −

Vasquez and Hanbury 2011 Y Y N Y Y N − N − − − − − − − − − − − −

Widiyanto et al. 2002 Y Y Y Y N − − N − − − − − − − − − − − −

Wong and Tan 2014 Y Y Y Y Y N − N − − − − − − − − − − − −


Table A-8. Description of Screening Columns

Column Criterion Description

First Screen

A Written in 1980 or later?

B Full text available?

C Not abstract, poster, slideshow, conference paper <5 double-spaced pages, trade journal article <3 published pages?

D Written in English or translated version available?

E Covers geothermal energy?

F Performs or reviews LCA(s) and provides quantitative results?

G Evaluates electricity as an end product?

P1 Passes screen 1?

Second Screen

H Uses currently accepted LCA method?

I Employs a relevant impact assessment method?

J Examines at least two life cycle stages?

K Provides reasonable description of methods?

L Cites data sources?

M Reports a unique result?

N If appropriate, reports name of software or database used for analysis?

O Describes system characteristics quantitatively?

P Reports environmental impact estimates quantitatively?

Q Employs enough detail to scale results to per kWh?

R Examines modern or near-future system?

P2 Passes screen 2?


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